The Problem We Solve
We are an Applied Intelligence company. We apply intelligence systems to hard, data-rich problems — starting with fashion commerce, working with brands and marketplaces.
Fashion is where Multimodal AI has the most to offer. Everything that matters in fashion — what a product looks like, how it reads in context, what a buyer responds to, what is trending before the data catches up — is visual, contextual, and impossible to capture in structured fields. Our expertise in Multimodal AI runs deepest here, and that is where we are focused first.
Our core technical expertise: Multimodal Search and Recommendation Systems, Fashion Trend Detection and Forecasting, and Production-grade Agentic AI.
Fashion brands and marketplaces generate more data than any analyst can process. Product images, search queries, sell-through signals, trend velocity, catalog gaps. Most of it goes unused. The tools that exist were built for general retail, not for how fashion actually works.
We build the systems that make that data useful — and we deploy them inside your organization, not on top of it.
What We Do
Know what is selling, where, and why — before it shows up in your weekly report.
Identify what is gaining momentum in the market before it reaches your buyers' desks.
Close the gap between what your customers are searching for and what your catalog actually shows them. We published the first open benchmark proving a properly built search pipeline delivers over 80% better results than standard approaches. Read the research.
Turn inconsistent product data into structured, searchable records at scale. Perfectly SEO-ed and AEO-ed, with metadata flowing directly from Commercial and Trend Intelligence.
Connect what you make to the customers most likely to buy it. Ecosystem completion for fashion with perfectly optimised Growth Marketing Intelligence.
Agentic AI problems you cannot solve and think they might challenge us. Bring it on. Connect with us.
Fashion Intelligence, Not General AI
Fashion is not a soft domain.
A general-purpose model does not know the difference between a trend that is ascending and one that peaked eighteen months ago. It cannot evaluate whether a catalog attribute is missing or just named differently. It does not understand how a buyer makes a decision or what makes a visual search result wrong in a way that matters.
We built our datasets, benchmarks, and evaluation criteria from scratch for this vertical. That is not a differentiator we claim. It is work we have published openly and that anyone can verify.
How We Work
We are not a SaaS vendor. We are not a consulting firm.
We embed engineers directly in your team — in your codebase, your data environment, on your infrastructure — until the system is running in production and your team can operate it without us.
Your data never leaves your environment. We work where your data lives, not the other way around. Every model we train on your catalog, your sales history, or your design assets belongs to you and is deployed on your infrastructure. We do not aggregate client data, we do not train shared models across clients, and we do not retain access after an engagement ends.
Every engagement closes with something your organization owns outright and can operate independently.
Start a conversationBuilt in the Open
What we open source is infrastructure. The underlying pipelines, search architectures, embedding models, and agentic frameworks we build when solving problems that have broad applicability beyond any single client. MIT licensed, on GitHub, and anyone can build with it.
What never leaves your organization: your product data, your sales data, your design files, your catalog, your trend signals, your customer behavior. None of it is used to train shared models. None of it is shared with other clients. None of it appears in anything we publish.
The distinction is deliberate. Generic infrastructure benefits from being open. Your data is your competitive advantage and it stays that way.
Explore our infrastructure on GitHubThinking Out Loud
We write about what we are working on and what we are learning — fashion AI, search systems, the things that did not go as expected.
Read on SubstackWork With Us
If you are running a fashion brand and your data is not working as hard as it should be, we want to understand the problem before we talk about solutions.
Start a conversationJoin Us
Small team. Hard problems. We write to figure things out and ship things people use. If that sounds right, get in touch.